u

      """

      return np.interp(x,self._x,self._eff,left=0.,right=1.)

   #

   def sampled_pdf(self,x,method='hist') :

   def sampled_pdf(self,x,method='hist',density=False) :

      """returns the sample pdf for a list of x

         output: hh, xx

         if method = 'hist' the pdf is calculated using an histogram like function (default)

         if method = 'tan' the pdf is calculated using the local tangent to the cdf

         if method = 'hist' and density = True, hh is normalized to the step size and represents an approximation of the local derivative

      """

      if not method in ['hist','tan'] :

         raise Exception("Error: method must be either 'hist' or 'tan'")

            _x=np.sort(x)

         #

         yy=self.cdf(_x)

         hh=(yy[:-1]-yy[1:])/(_x[:-1]-_x[1:])

         hh=(yy[1:]-yy[:-1])/(_x[1:]-_x[:-1]) if density else yy[1:]-yy[:-1]

         return hh, _x

      elif method == 'tan' :

         h=(self._x[-1]-self._x[0])*eps